S. Arbiv, R. Amin, T. Goff, Downing Street, Igor Pedan, L. Bressler, Terrence Gibbons, Bow-Nan Cheng, Chayil Timmerman
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引用次数: 3
摘要
美国国防部(DoD)在开发和部署空中高容量骨干网(HCB)方面投入了大量资金。理解这些移动自组织网络(manet)的性能具有挑战性,并且需要深入了解协议栈的多个层。在堆栈的每一层都会产生大量的数据。麻省理工学院开发了一个数据收集和可视化框架来解析重要数据,并帮助监控和分析这些网络的性能。HCB数据收集和分析框架由可插拔的数据收集和报告守护进程、基于时间序列数据库的持久存储组件以及能够以实时和回放模式显示网络性能指标的可视化仪表板组成。在本文中,我们展示了这个框架的功能,确定它如何帮助我们进一步的研究,以及如何适应它来支持其他产生大量数据的类似研究项目。A.批准公开发行。分发是无限的。本材料是根据空军合同No. 1的规定由海军部支持的工作。fa8702 - 15 d - 0001。本材料中表达的任何观点、发现、结论或建议均为作者的观点,并不一定反映海军部的观点。
Data Collection and Analysis Framework for Mobile Ad Hoc Network Research
The U.S. Department of Defense (DoD) has invested significantly in development and deployment of aerial high-capacity backbone (HCB) networks. Understanding the performance of these Mobile Ad-Hoc Networks (MANETs) is challenging, and requires insight into multiple layers of the protocol stack. Tons of data get generated at each layer of the stack. MIT LL has developed a data collection and visualization framework to parse through important data and help monitor and analyze the performance of these networks. The HCB data collection and analysis framework is comprised of pluggable data collection and reporting daemons, a persistent storage component based on a time-series database, and a visualization dashboard capable of displaying network performance metrics in real-time and playback modes. In this paper, we showcase the capabilities of this framework, identifying how it has helped further our research, and how it can be adapted to support other similar research programs that generate tons of data. 11DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Department of the Navy under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Navy.